R Notebook

rr library(dplyr)

Attaching package: ‘dplyr’

The following objects are masked from ‘package:stats’:

    filter, lag

The following objects are masked from ‘package:base’:

    intersect, setdiff, setequal, union

rr wolfrum <- readRDS(‘/projects/timshel/sc-scheele_lab_adipose_fluidigm_c1/data-wolfrum/wolfrum.compute.seurat_obj.rds’)

What do the clusters represent?

rr pos_markers_top20 <- markers %>% group_by(cluster) %>% top_n(n=6, wt=avg_logFC) %>% unite(col=‘cluster_gene’, c(cluster, gene), remove=F)

neg_markers_top20 <- markers %>% group_by(cluster) %>% top_n(n=6, wt=desc(avg_logFC)) %>% unite(col=‘cluster_gene’, c(cluster, gene), remove=F)

rr plots <- FeaturePlot(wolfrum, features=as.vector(pos_markers_top20\(gene[1:6]), combine = FALSE, pt.size=1) for(i in 1:length(plots)) { plots[[i]] <- plots[[i]] + ggtitle(pos_markers_top20\)cluster_gene[i]) + NoAxes() }

rr plot_grid(plotlist=plots, ncol=3)

U and L branch markers.

rr FeaturePlot(wolfrum, features=c(‘UCP2’, ‘FABP5’, ‘G0S2’, ‘FABP4’, ‘ADIPOQ’, ‘ADIRF’, ‘CD36’, ‘PLIN4’, ‘APOD’, ‘MGP’, ‘DCN’, ‘CTGF’, ‘IGF2’, ‘CCDC80’, ‘PLAC9’, ‘THBS1’), cols=c(‘gray’, ‘blue’), ncol = 2, reduction=‘umap’, pt.size=1)

Preadipocytes

rr FeaturePlot(wolfrum, features=c(‘TMSB4X’), cols=c(‘gray’, ‘blue’), ncol = 2, reduction=‘umap’, pt.size=1)

Monocle

Ran Monocle on the Wolfrum subset with the same gene list that was used to build the 10x-180831 trajectory.

monocle_results <- readRDS('../output/monocle/wolfrum/wolfrum_subset.compute.seurat_obj.rds-monocle-monocle_genelist_T1T2T3_T4T5_res.1.5')

  return(df)

Error: no function to return from, jumping to top level

states.prediction

     n Metabolic  ECM Progenitor
1 3242      0.96 0.01       0.03
2 2385      0.09 0.84       0.07
3 1605      0.64 0.09       0.28